Predictions for Ultra-Deep Radio Counts of Star-Forming Galaxies

Mancuso, C., Lapi, A., Cai, Z., Negrello, Mattia ORCID: https://orcid.org/0000-0002-7925-7663, De Zotti, G., Bressan, A., Bonato, M., Perrotta, F. and Danese, L. 2015. Predictions for Ultra-Deep Radio Counts of Star-Forming Galaxies. The Astrophysical Journal 810 (1) , p. 72. 10.1088/0004-637X/810/1/72

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Abstract

We have worked outty predictions for the radio counts of star-forming galaxies down to nJy levels, along with redshift distributions down to the detection limits of the phase 1 Square Kilometer Array MID telescope (SKA1-MID) and of its precursors. Such predictions were obtained by coupling epoch-dependent star formation rate (SFR) functions with relations between SFR and radio (synchrotron and free–free) emission. The SFR functions were derived taking into account both the dust-obscured and the unobscured star formation, by combining far-infrared, ultraviolet, and Hα luminosity functions up to high redshifts. We have also revisited the South Pole Telescope counts of dusty galaxies at 95 GHz, performing a detailed analysis of the Spectral Energy Distributions. Our results show that the deepest SKA1-MID surveys will detect high-z galaxies with SFRs two orders of magnitude lower compared to Herschel surveys. The highest redshift tails of the distributions at the detection limits of planned SKA1-MID surveys comprise a substantial fraction of strongly lensed galaxies. We predict that a survey down to 0.25 μJy at 1.4 GHz will detect about 1200 strongly lensed galaxies per square degree, at redshifts of up to 10. For about 30% of them the SKA1-MID will detect at least 2 images. The SKA1-MID will thus provide a comprehensive view of the star formation history throughout the re-ionization epoch, unaffected by dust extinction. We have also provided specific predictions for the EMU/ASKAP and MIGHTEE/MeerKAT surveys.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Physics and Astronomy
Subjects:	Q Science > QC Physics
Publisher:	IOP Publishing
ISSN:	15384357
Last Modified:	31 Oct 2022 10:11
URI:	https://orca.cardiff.ac.uk/id/eprint/83992

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